Wisran is a revolutionary startup idea,selected by MIT boot camp.It uses data sciences to measure time variations of framing.


Limited time and budget

Provided with all of its complexity,we had to prove our idea, by developing a minimum viable product,within a season i.e. 3 months as we didn’t have enough budget to record data of whole year farming cycle covering all processes and seasons.

Real-time activity mapping

As different industrial farming vehicles,each having different sizes,speed and movement actions were involved even in a single process,identification of current activity was dependent on a number of variables.We had to develop a rule engine for analyzing a large set of variables and determining current activity and its relative stage.


Scalability was a real challenge as adding a single node in the system adds a huge volume of data.We had to design a totally decoupled architecture that keeps all software components,along the data pipeline and data aggregation engine in their optimally efficient state and ensures the analysis,aggregation and computation on a huge set of data provides a real-time picture.

Complex Business Domain

Farmers use slight variations of a single process based on their experience,field size,farm size and budget etc.In 1st place, a large volume of raw data was available to understand and experiment.With the help of this raw data, understanding all variants of processes and identifying inefficiencies in them, was itself a great challenge.
Wisran is live with an Android and an iOS app.It has now successfully automated 56713 acres of industrial agriculture fields and made its way to Australia by winning a grant from the Australian government.


Limited time and budget

Our years-long experience of managing medium and large complex projects helped us keep this project on its planned trajectory. We followed Agile processes and divided relevant stories in sprints with complete focus on adding maximum business value in each sprint.

Real-time activity mapping

We used Apache Kafka and Nifi to receive and channelize data streams,being relayed towards our rule engine powered by Apache spark, that analyzed and made aggregations based on complex rules at great speed.


The decoupled infrastructure design rescued us. We designed the system in three layers, a data pipeline, a core engine and a data layer.Each of these layers is a multi-node system and we can add multiple nodes in each layer according to the system demand, anytime.

Complex Business Domain

Our onsite manager visited the original site and conducted dozens of interviews with clients, business stakeholders and vehicle operators. Various interactive meetings and brainstorming sessions were held. With the well-organized collaborative effort, we were able to convert business requirements to stories and epics.

Equipment Monitoring:

It helps to remotely check the mixed fleet of various models of trucks and other equipment.

Automated Guidance:

Automated guidance related to the inefficiency of the field is provided to offer more jobs in less time.

Analysis of Financial Impact:

WISRAN uses technology for analyzing the financial effects of fieldwork performance.

Maximum Profit:

The actual time and cost per acre are tracked to get the maximum profit.


Technology stack



  Swift 4


Kotlin/Java 7


Web (Admin panel)

Node JS8

Angular 2









Production server:




Apple Store

Wisran Review

Arslan Lodhi
C.E.O Wisran

Big thanks to my software engineering crew in Ukraine – developers, engineers, database specialists, designers, QAs – all of whom have been working hard with me over the last nine months on the new and re-powered MILANSTYLE.com. Something like 800,000 products from the world’s best luxury stores in one place Wow. A few further things we plan to do, tweak and enhance, but ecommerce and large database-driven websites are always a work in progress. Team work makes the dream work.

Do you want anything like that?

Do you want anything like that?